About Me

Hello, I am a Ph.D student at Machine Learning and Intelligence Lab (MLILAB) in KAIST, advised by Prof. Eunho Yang.

My research focuses on enhancing the efficiency of foundation models, particularly auto-regressive generative models. I aim to improve inference-time efficiency by optimizing memory usage and reducing latency, leveraging techniques such as speculative decoding and knowledge distillation, among others.

Publications

• LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding [paper]
  Doohyuk Jang*, Sihwan Park*, June Yong Yang, Yeonsung Jung, Jihun Yun, Souvik Kundu, Sungyub Kim, Eunho Yang
  ICLR 2025

• PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning [paper]
  Gyeongman Kim, Doohyuk Jang, Eunho Yang
  Findings of EMNLP 2024

• SeamsTalk: Seamless Talking Face Generation via Flow-Guided Inpainting [paper]
  Yeongho Jeong, Gyeongman Kim, Doohyuk Jang, Jaeryong Hwang, Eunho Yang
  IEEE Access 2024

• Med-PerSAM: One-Shot Visual Prompt Tuning for Personalized Segment Anything Model in Medical Domain [paper]
  Hangyul Yoon, Doohyuk Jang, Jungeun Kim, Eunho Yang
  Under Review

Education

• Ph.D. in Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Sep. 2024 - Present

• M.S. in Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Mar. 2023 - Aug. 2024

• B.S. in Electrical Engineering, Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Mar. 2018 - Feb. 2023

Work Experiences

• Intern, Synopsys Korea, Gyeonggi, South Korea, Mar 2021 - Aug 2021

Projects

• Developing a conversational language model for virtual doctors, AITRICS, Apr. 2024 - May. 2024

Acamdeic Services

• Workshop Reviewer
  • SCOPE@ICLR 2025

Teaching Experience

• Teaching Assistant, Machine Learning for AI (AI501), KAIST